You are viewing a plain text version of this content. The canonical link for it is here.
Posted to reviews@spark.apache.org by GitBox <gi...@apache.org> on 2020/10/17 03:56:26 UTC

[GitHub] [spark] zsxwing commented on a change in pull request #30073: [SPARK-33170][SQL] Add SQL config to control fast-fail behavior in FileFormatWriter

zsxwing commented on a change in pull request #30073:
URL: https://github.com/apache/spark/pull/30073#discussion_r506790079



##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala
##########
@@ -2052,6 +2052,20 @@ object SQLConf {
       .stringConf
       .createWithDefault("")
 
+  val FASTFAIL_ON_FILEFORMAT_OUTPUT =
+    buildConf("spark.sql.execution.fastFailOnFileFormatOutput")
+      .internal()
+      .doc("Whether to fast fail task execution when writing output to FileFormat datasource. " +
+        "If this is enabled, in `FileFormatWriter` we will catch `FileAlreadyExistsException` " +
+        "and fast fail output task without further task retry. Only enabling this if you know " +
+        "the `FileAlreadyExistsException` of the output task is unrecoverable, i.e., further " +
+        "task attempts won't be able to success. If the `FileAlreadyExistsException` might be " +
+        "recoverable, you should keep this as disabled and let Spark to retry output tasks. " +
+        "This is disabled by default.")
+      .version("3.1.0")

Review comment:
       I think it's better to merge to branch-3.0 as well as currently user don't have a flag for this in 3.0.x.




----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.

For queries about this service, please contact Infrastructure at:
users@infra.apache.org



---------------------------------------------------------------------
To unsubscribe, e-mail: reviews-unsubscribe@spark.apache.org
For additional commands, e-mail: reviews-help@spark.apache.org